Machine learning allergy risk diagnosis determination

A computer program product, comprising a computer readable hardware storage device storing a computer readable program code, said computer readable program code comprising an algorithm that when executed by a processor of a server hardware device implements a machine learning allergy risk diagnosis improvement method, said method comprising:

• identifying, by said processor, a plurality of databases comprising data identifying menu items served by a plurality of food establishments;
• first analyzing in real time, by said processor executing natural language software code, allergy data defining a plurality of food products associated with a plurality of potential allergens;
• generating, by said processor based on results of said analyzing, baseline allergen indication software code for defining an allergen baseline indicator;
• second analyzing in real time, by said processor executing said natural language software code and said baseline allergen indication software code, ingredients of said menu items with respect to said allergy data;
• determining, by said processor based on results of said second analyzing in real time, allergen baseline levels for said ingredients of said menu items;
• determining, by said processor, an allergen baseline levels for each menu item of said menu items;
• and
• generating, by said processor, an allergen alert software application for alerting users with respect to each said overall allergen assessment.

A server hardware device comprising a processor coupled to a computer-readable memory unit, said memory unit comprising instructions that when executed by the computer processor implements a machine learning allergy risk diagnosis improvement method comprising:

• identifying, by said processor, a plurality of databases comprising data identifying menu items served by a plurality of food establishments;
• first analyzing in real time, by said processor executing natural language software code, allergy data defining a plurality of food products associated with a plurality of potential allergens;
• generating, by said processor based on results of said analyzing, baseline allergen indication software code for defining an allergen baseline indicator;
• second analyzing in real time, by said processor executing said natural language software code and said baseline allergen indication software code, ingredients of said menu items with respect to said allergy data;
• determining, by said processor based on results of said second analyzing in real time, allergen baseline levels for said ingredients of said menu items;
• determining, by said processor, an allergen baseline levels for each menu item of said menu items;
• and
• generating, by said processor, an allergen alert software application for alerting users with respect to each said overall allergen assessment.